Antelop

A database for systems neuroscience foundation models

Rory Bedford

MRC LMB

Foundation models in neuroscience

  • Large machine learning models that learn the relationship between neural activity, sensory inputs and motor outputs
  • Trained via self-supervised learning methods such as masked modelling
  • Can be fine tuned to perform a number of prediction tasks
  • Require extremely large datasets, well structured and preprocessed

Data engineering

  • Increasingly large datasets within systems neuroscience (e.g. Neuropixels)
  • Data storage needs to keep up with data engineering best practices
  • Custom file formats/project structures are hard to parse
  • Data preprocessing pipelines becoming increasingly complex and computationally expensive
  • Custom preprocessing/analysis scripts are very difficult to reproduce
  • High entry barrier to existing tools like DataJoint and NWB which makes their adoption difficult for many labs

Our solution: Antelop

  • Software package designed to facilitate the easy adoption of data processing and storage best practices
  • Simple pip install and straightforward graphical configuration
  • Extensive graphical user interface for all aspects of your data management and processing
  • MySQL database backend for centralised storage
  • Supports electrophysiology, calcium imaging, and behavioural data processing with HPC integration

Our solution: Antelop

  • Integrates with existing tools, such as popular spikesorters, CaImAn, and DeepLabCut
  • Implements a range of data visualisation tools and metrics out of the box, including an analysis standard library
  • Supports the writing of custom analysis scripts, with direct integration to your lab’s GitHub and data immutability checks for reproducibility
  • Has import/export functions for NWB and a range of acquisition systems
  • Has an opinionated but accomodating database structure for ML models to utilise

Publishing

  • Working on a preprint at present
  • We aim to publish by May this year
  • Python package has been released but is undergoing extensive testing

Thank you